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CORR
2006
Springer
153views Education» more  CORR 2006»
14 years 11 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
BMCBI
2010
165views more  BMCBI 2010»
14 years 12 months ago
MTar: a computational microRNA target prediction architecture for human transcriptome
Background: MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in importa...
Vinod Chandra, Reshmi Girijadevi, Achuthsankar S. ...
ICCV
2009
IEEE
16 years 4 months ago
Efficient subset selection based on the Renyi entropy
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...
DIS
2005
Springer
15 years 5 months ago
Support Vector Inductive Logic Programming
Abstract. In this paper we explore a topic which is at the intersection of two areas of Machine Learning: namely Support Vector Machines (SVMs) and Inductive Logic Programming (ILP...
Stephen Muggleton, Huma Lodhi, Ata Amini, Michael ...
COLT
1995
Springer
15 years 3 months ago
Regression NSS: An Alternative to Cross Validation
The Noise Sensitivity Signature (NSS), originally introduced by Grossman and Lapedes (1993), was proposed as an alternative to cross validation for selecting network complexity. I...
Michael P. Perrone, Brian S. Blais